Positioning with navigation satellite signals is well-proven in open localities, but it is practically incapable indoors. The cause is weakening of the satellite signal following its passing through walls, ceilings and floors of the buildings to such an extent that its level is inadequate for receipt by the satellite receiver in most cases. Even in the cases when the satellite signal is not as weak, it is attenuated due to reflections from indoor walls and other things (effect of multi-beam propagation of radio-waves), this results in intolerably large navigation errors.
The prior art knows technical solution U.S. Pat. No. 6,323,807, Indoor Navigation with Wearable Passive Sensors, Mitsubishi Electric Research Laboratories, published on 27 Nov. 2001. This solution describes the technique of indoor navigation with alternative, not satellite, sources of navigation data, in accordance with this solution, first a map of conformity between the positions with known coordinates of the positioned object, which may be a mobile terminal, and the data obtained in these positions from non-inertial sensors, is issued, subsequently, in the process of further flow, similar non-inertial data are acquired in unknown positions, compared with data obtained in the known positions, the known position is detected with data which are as close as possible to data acquired in the unknown position, whereafter the unknown position of the mobile terminal may be considered as equal to detected known position. Non-inertial data acquired in the time moments when the mobile terminal position was known together with information on these positions may generate a special map or data base different from standard indoor environment layout solely with a specific nature of mapped data. Such maps are commonly referred to as the ‘fingerprinting’. Data acquired from non-inertial sensors in the reviewed technique may be Wi-Fi signals obtained from access points observed by the mobile terminal, magnetic detector readings, images obtained from video-camera of the mobile telephone and any other data available for the mobile device allowing for direct or indirect detection of user's location. To increase accuracy of positioning, the described technique may allow for usage of data obtained from inertial sensors based on dead reckoning (the term Dead Reckoning). The weak point of this technique may be required full mapping of indoor environments which is expensive and not always practicable. The other disadvantage of this technique may be required indication of coordinates of known positions in the process of training which requires utilization of the other, more highly precise technique for detection of mobile terminal coordinates in the indoor environments.
Simultaneously with positioning technique, the said technical solution describes the positioning device comprising passive sensors of the mobile terminal, a portable computer and a module for estimation of probability of conformity of the unknown position with one of the known positions. The system described in this technical solution is the closest to the proposed one and is selected as a prototype.
The technical solution, described in application WO2013038005, Method for Localization and Mapping of Pedestrians or Robots Using Wireless Access Points, Deutsches Zentrum fuer Luft- and Raumfahrt e. V., published on 21 Mar. 2013, is known. This application describes the technique for mapping and subsequent indoor positioning with Dead Reckoning qualitative algorithm based upon inertial sensors and an odometer. The advantage of this technique may be independent detection of positions in the process of acquisition of data for mapping. The disadvantage of the described technical solution may be utilization of special equipment in the process of mapping data acquisition, as well as required performance of mapping activities, expensive and not always practicable.
The technical solution described in application US20130293416A1, Apparatus and Method for Indoor Positioning, Texas Instruments Incorporated, published on 7 Nov. 2013, is known. The specified application describes the technique for mapping and indoor positioning in accordance with which the known positions are detected with satellite signals prior to enter the indoor environments, subsequently, indoor positions are computed with inertial sensors, data obtained from non-inertial sensors are entered for these positions into the data base, then in the process of subsequent flow, coordinates of the mobile terminal in the unknown position are computed by comparison of new non-inertial data with data shown in the map. The advantage of this technique may be full automation and practicability of mapping without any additional equipment. Mapping may be implemented by people in the process of every-day movement. In theory, this technique, called ‘crowd-sourcing’ in the literature may allow for mapping of all indoor environments, but not only individual ones, where special activities have been performed with the above techniques. The disadvantage of this approach may be degradation of accuracy of the position computed with inertial sensors as far as the mobile terminal moves indoors, as well as lack of sufficient information for estimation of dead reckoning accuracy in accordance with the data obtained from inertial sensors. As a consequence, much non-inertial data with positions detected not accurately get into the map, this makes the mapping process more complicated and subsequent positioning less accurate.
The technical solution, described in application WO2013165391A1, Simultaneous Localization and Mapping Using Spatial and Temporal Coherence for Indoor Location, Intel Corporation, published on 7 Nov. 2013, is known. This application describes the technique for mapping with users' occasional walking tiles forming the closed paths. To detect path self-crossing (return to already passed position in the patent terms), time moments when new data obtained from non-inertial sensors (hereinafter referred to as the ‘non-inertial’ data) are correlated adequately with similar data obtained some time ago, are searched for, as well as time moments when the path computed with the data obtained from inertial sensors (hereinafter referred to as the ‘inertial’ data) crosses itself or contains adjacent areas are searched for, and should the moments of proposed self-crossing computed in accordance with non-inertial data coincide with moments computed with inertial data, a conclusion on fitness of acquired navigation data for subsequent analysis is made. This analysis may consist of updating of the path computed with inertial data, comparison of tracks acquired in such a way and their association in the continuous map via alignment of those track sections where similar non-inertial data were observed. The advantage of this approach may be more accurate mapping achieved due to analysis and updating of used navigation data. The other advantage of this technique may be practicability of mapping of large indoor environments which are impractical to enter from outside quickly (especially from outdoors). The disadvantage of this technique may be improved but still weak protection against poor quality data, as well as unsolved problem how to detect and correlate coordinates of mapped data. Noisy mapped data with inaccurate reference to the layout when they are linked into a single map may result in higher mapping error. Utilization of such map may result in great positioning errors.
The said application describes the device for positioning of the mobile terminal comprising a set of comparators analyzing isolated flows of inertial and non-inertial data with regard to their recurrence of the same or similar values spread out over some time period and detecting excess of similarity of data of a specific threshold.
In addition, the prior art has a large number of techniques for indoor positioning of the mobile terminal without reference to indoor environment coordinates. Such techniques may include, for example, beacon positioning—Bluetooth Low Energy (BLE), tag positioning—Near Field Communication (NFC), transmitter positioning—Indoor Messaging System (IMES), 2D matrix Quick Response (QR) code positioning. In some cases, an already generated infrastructure may be enough. These techniques do not require mapping, which is their advantage. However, positioning only in individual indoor areas is provided, which together with low positioning accuracy, represents the disadvantages of such techniques.